national conference - big data - 31 jan 2015

Big Data Technical Overview

31 Jan 2015

Big Data : Crystal Ball of Success National Conference - Information of Technical Infrastructure at Hiraben Nanavati Institute of Management and Research for Women


Presenter

Over 16 years of IT experience Help business in designing their data architecture and information

roadmap Help business in identifying their performance metrics and

designing it through data and winning business. Worked globally and delivered key businesses to the Retail, Banking

and Manufacturing. Key Big Data Implementation : Sears & Roebuck Co., Bank of

America etc. A technical expert, Sr. Data Architect/Data Scientist with strong

Banking, Retail and Telecom domain experience Responsible for Big Data management and leading the Pioneer

project using Hadoop Engaged with Technology stack like Teradata, Netezza,

Microstrategy, Cognos, Big Data etc. MBA in Marketing giving edge to the business governance and

business objectives Business Community focus with Technology help Expert in building and Leading skilled resources to enable business

success.

1

______________________________________ Sanjiv Kumar, Technology Evangelist, Big Data & Data Science, Zensar Technologies Limited Mobile: +91 9028837503 Landline : +91-20- 4071 3274 Email : [email protected] | Website: www.zensar.com | LinkedIn: http://in.linkedin.com/in/sanjiv123/ ______________________________________

Big Data Video

mailto:[email protected]

http://www.zensar.com/

http://in.linkedin.com/in/sanjiv123/


What is Big Data

2

Big

Data for

Dummies

Big Data is a tool that allows any company the ability to accurately analyze its data.

Big Data Technical Overview 3

New Sources of Data


How data is born and growing?


Magic mirror of data


Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the

structures of your database architectures. To gain value from this data, one must choose an

alternative way to process it.

Defnition of Big Data


Market opportunity

Walmart handles more than 1 million customer transactions every hour.

Facebook handles 40 billion photos from its user base.

Decoding the human genome originally took 10years to process; now it can be achieved in one week.


The Data Explosion


Who uses BIG DATA ANALYTICS

Manufacturing Trading Analytics Fraud and Risk Retail: Churn, NBO

Finance Smarter Healthcare Multi-channel sales Log Analysis

Homeland Security Telecom Traffic Control Search Quality

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BUSINESS VALUE : Retail Industry

Retailer are flooded with data from sources such as web logs , social media , Point Of Sale (PoS) and online sales data (credit card and reward card purchases) , in-store video footage , search data , foot traffic , RFID etc.

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Enhance customer profiling and segmentation for

better targeted sales, enabling better customer

retention rates

Real time analysis to market responses to price – product changes, enabling optimal pricing and stocking

Enable calculation of cross elasticity of demand

Real time analysis of customer behavior and purchase patterns resulting in accurate appraisal of customer lifetime value

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• Distribution and logistic optimization

• Management supplier negotiations Supply Chain &

Procurement

• Assortment & Price Optimization

• Store Layout Merchandising

• Performance transparency

• Labor Inputs Operations

• Cross Selling

• Sentimental Analysis

Sales & Marketing

• Customer behavior analysis Customer Service

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Indian service providers like Infosys , Fractal are providing retailers Big Data Implementation and analytics services for campaign management , sentimental analysis , inventory management etc…


BUSINESS VALUE: Manufacturing Industry

The manufacturing sector has witnessed many advancements in streamlining processes and improvements in quality. Big data provides it the next wave of enhancement particularly in supply chain responsiveness , monitoring equipment and R&D.

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• Product Development

• Customer Collaboration

• Integrating datasets

R & D

• Improve responsiveness of supply chain management

• Inventory optimization Procurement

• Enterprise asset management

• Digital shop floor control

• Operation cost forecasting

Production

• Customer Relationship Management

• Marketing Campaigns

• Customer segmentation

Sales & Distribution

• Real –time analysis of after sales and feedback data

• Warranty analysis After Sales Service

• Improves demand forecasting and supply planning through real time planning

• Enables collaboration engineering through crowd sourcing that significantly cuts time –to – market and improves quality

• Enables design to value , improvement in output quantity and facilitates mass customization

• Better product lifecycle management, job scheduling and service levels

• Real –time detection


BUSINESS VALUE: Finance Industry

Customer and transaction data from multiple channels like branch, kiosks, mobile, web , social media, emails , credit cards data, insurance claims data , stock market data , statistical data , PDF & excel files , news , videos, government filings,… etc. are key Big Data sources ……

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Risk Management / Assessment

Trading Surveillance

Banking Capital Markets

Trading Insurance

Credit Line Optimization

Credit reward analysis

Pre –trade decision support analysis

Fraud Detection

Portfolio Analytics

Compliance & Regulatory Reporting

Customer Relationship Management

Consumer Behavioral Patterns

Predict client longevity

Trading Pattern Analysis

Intra- day Analysis

Using weather & calamity

information for managing losses

• Detect , prevent and remedy financial fraud in real – time

• Accurate risk assessment of customers credibility and financial position

• Effective trade monitoring and analysis

• Adhering to stringent compliances and provide granular reporting to regulators

• Enhance customer experience through personalized products and services

• Execute high value marketing campaigns

• Reduce cost and discover new revenue opportunities

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BUSINESS VALUE: Healthcare Industry

Healthcare players create terabytes of structured and unstructured data through growing digitalization of healthcare, the monitoring of in-patient and out-patent through sensors , epidemic data and the mass sequencing of the genome is generating huge amount of data.

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• Improved quality of patient care, proactive care

• Lower cost of healthcare services and patient care

• Enhanced fraud detection and efficient hospital operations

• Big Data Implementation in healthcare is expected to gain traction

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• Drug Discovery, data annotations and validity analysis

• Study of gene expression for next generation sequencing

R & D , Life Sciences / Bio Medicines

• Patient monitoring and assessment

• Patient care personalization

• Provide effective value added services

Patient Care

• Influence consumer behavior

• Optimize physician interactions

• Clinical decision support

Healthcare Operations

• Health issues trend analysis across geographies , tracking spread of diseases

Epidemiology

• Fraud detection Healthcare Security


What’s diiferent is this time


Why we use Hadoop

Hadoop Use Cases

Reducing infrastructure costs

New analytics on existing data

Expanding data for existing applications

Combining different data sources

New application from new data sources

Power of distributed computing

Power of parrallel processing

Power of comodity hardware

How do Hadoop does it?


Big Data can create value in a broad range of industries Long list of opportunity identified

17

Vertical Application (industry specific)

Financial Services

Risk mgmt Fraud detection Improve debt recovery rates Personalize banking

products Mktng

effectiveness Micropayments Improve

customer service Churn

prevention Customer

segmentation Smarter trading Improve

underwriting Gamification of

savingss

Retail / Consumer

Near real-time

pricing Stock keeping &

replenishment optimization

Store layout optimization

In-store behavior analysis

Cross selling

Optimize pricing, placement, design

Performance transparency

Customer service

Inventory mgmt.

TMT

Customer insight based targeting (offers, advertising)

Social network analysis

Churn management in elcos

Reduce downtime for systems

Public Sector

Reduce fraud

Segment populations, customize action

Support open data initiatives

Automate decision making, improve event response

Healthcare

Clinical decision support

Outcomes benchmarking

Life sciences research

Optimal treatment pathways

Remote patient monitoring

Predictive modelling for new drugs

Personalized medication

Improved diagnostics, hospital ops

Insurance

Usage based insurance (PAYD1)

Fraud detection

Niche products and insurance bundles

Customer knowledge

Intelligent insurance renewa

Big Data to calculate insurance premium

Energy

Natural

resource exploration

Demand response optimization

Maintenance and drilling optimization

Micro weather forecasting

Optimize asset location

Transportation

Traffic &

congestion management

Travel assistance

Fleet/network optimization

Preventive maintenance of fleets

Industrial Goods

Data driven product design

Shop-floor optimization

Agile supply chain mgmt.

Design to value

Crowd-sourcing

"Digital factory" for lean manufacturing

Improve service via product sensor data

Location-based marketing

Social Segmentation Social Media / Other Application

Sentiment Analysis

Price Comparison Service


Smart Cities


Thank You

national conference - big data - 31 jan 2015

Documents

big data data science

big data management

dummies big data

search data

data architecture

key big data implementation

data architectdata scientist

online sales data credit